arXiv (All)
open access
Set-based state estimation of nonlinear discrete-time systems using constrained zonotopes and polyhedral relaxations
This paper presents a new algorithm for set-based state estimation of nonlinear discrete-time systems. A key step in such algorithms is to propagate a set (often a zonotope or constrained zonotope) through a nonlinear function. Existing methods accomplish this through conservative linearization proc
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- On Solving Continuous-Discrete Projection Filters via Sum-of-Squares Relaxation#784773
- On Solving Continuous-Discrete Projection Filters via Sum-of-Squares Relaxation#783183
- Linear Programming Representations and Strongly Polynomial Algorithms for Robust Markov Decision Processes#1161031
- Linear Programming Representations and Strongly Polynomial Algorithms for Robust Markov Decision Processes#1157479
- Discrete-time feedback linearization control for nonsmooth constrained optimization#1077726
Record · ID 986774
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive